AI-powered video pipeline
Drag & drop video, or click to browse
MP4, MOV, MKV — any size
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Trim applied — pipeline will process only the selected range.
| Thumb | ID / File | Status | Stage | Created | Actions |
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No jobs yet.
No output files yet.
No clips data yet (pipeline must reach Highlight stage).
No heatmap data yet (needs completed transcription).
Engagement score per 30-second window. Green = high engagement.
No content generated yet (pipeline must fully complete).
No validation report yet.
No transcript available.
| # | Time | EXCITE | Burst | Voice | Perc | Beat | Status | Action |
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● clipped 💀 ◦ free | — |
Signals: ── EXCITE (composite) · ■ waveform · ■ HF · ■ burst · ■ voice · ■ beat · ◆ impact · ■ sub · ─ score · ▼ Δloud · ■ dead zone · ■ motion · ── WPM · │ CONV (multi-signal confluence) · ▾ CUT (audio-novelty cut points)
Click signal labels (left of timeline) to toggle layers. EXCITE bar above timeline shows uncovered peaks (▲) + captured clips (violet). 🎉 teal bands on ruler = reaction windows after kills. ⚡ PEAK badge on video = highlight incoming in <5s.
⚠ LLM unavailable — rule-based analysis
Point this at your local LiteLLM proxy. It works with Ollama, LM Studio, or any OpenAI-compatible endpoint.
Use Claude API directly (claude-opus-4-7 with adaptive thinking) for highlight detection. Enables the AI Studio pipeline mode — much smarter than LLM-based highlight detection, especially for complex gaming footage. Requires an Anthropic API key.
In AI Studio mode, Claude analyzes the full transcript + audio features together using extended reasoning to identify the most impactful highlight moments. Results load directly into the editor — no video render needed.
Enable to unlock the 🤖 AI Studio pipeline mode in the Start Job modal.
You can use different models for each stage. For JSON accuracy (highlights) use a model strong at structured output. For creative writing (commentary) any good instruct model works.
GPU mode — fastest. compute_type auto-upgraded to float16. Make sure the NVIDIA runtime is passed to this container.
CPU mode — BatchedInferencePipeline splits audio into chunks processed in parallel. beam_size=1 (greedy) is fastest; VAD filter skips silence.
threads/chunk × chunks = cores active
Removes dead air and long pauses from each rendered clip, tightening pacing automatically.
Loops a music file under the full edit. Sidechain ducking lowers music volume automatically when speech is detected.
Burn a text watermark onto every clip. Leave blank to disable.
9:16 vertical shorts are always exported. Enable additional crops per clip.
Translate burnt-in captions to another language via LLM. Leave blank for source language.
Provide video file paths on the server. They'll be normalized and prepended/appended to the full edit.
Automatically restarts from the failed stage. Traceback is saved to progress.log.
Provide OAuth2 credentials to enable one-click YouTube publish from job detail. Get credentials at console.cloud.google.com.
Star clips from any job to save them here for reuse across projects.
No clips saved yet. Open a job and star a clip to add it here.
⚠ Found duplicate files in groups
files — same size & duration
Drop stream files here or browse
Multiple files supported · MP4, MKV, MOV, AVI, WebM — no processing, just storage
Saved ✓
Exactly what happens inside the app, step by step.
| Purpose | Model | Why |
|---|---|---|
| Visual Analysis | llama3.2-vision:11b qwen2-vl:7b | Must accept base64 image input |
| Highlights / Validation | llama3.3:70b qwen2.5:72b | Strong JSON + long context |
| Commentary | llama3.3:70b phi4 · mistral-nemo | Creative writing, short output |
| Transcription | large-v3 (best) medium (faster) | faster-whisper, runs locally |
Loading… (needs at least one completed job)
No completed jobs yet. Run a job to see timing statistics.
Based on your job history, estimate how long a new job will take.
Estimate based on average of completed job(s). Actual time varies with video complexity.
Click Load Logs to check for OOM kills or crash reasons.
No OOM kills or errors found in kernel logs.
Click Refresh to load.
Click Check to inspect.
Cached:
Transcribes a clip of your last uploaded audio with different thread configs to find the fastest setup for your machine.
Tested on of audio · model:
Higher realtime ratio = faster. Green ≥ 4x, yellow ≥ 2x, red < 2x. Apply the best config to save it to Settings.
Select a job above to start cutting.